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首页> 外文期刊>European Journal of Medicinal Chemistry: Chimie Therapeutique >Discovery of new nanomolar peroxisome proliferator-activated receptor gamma activators via elaborate ligand-based modeling.
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Discovery of new nanomolar peroxisome proliferator-activated receptor gamma activators via elaborate ligand-based modeling.

机译：通过精细的基于配体的建模发现新的纳摩尔过氧化物酶体增殖物激活的受体γ激活剂。

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摘要

Peroxisome Proliferator-Activated Receptor gamma (PPARgamma) activators have drawn great recent attention in the clinical management of type 2 diabetes mellitus, prompting several attempts to discover and optimize new PPARgamma activators. With this in mind, we explored the pharmacophoric space of PPARgamma using seven diverse sets of activators. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing self-consistent and predictive quantitative structure-activity relationship (QSAR) (r2(71)=0.80, F=270.3, r2LOO=0.73, r2PRESS against 17 external test inhibitors=0.67). Three orthogonal pharmacophores emerged in the QSAR equation and were validated by receiver operating characteristic (ROC) curves analysis. The models were then used to screen the national cancer institute (NCI) list of compounds. The highest-ranking hits were tested in vitro. The most potent hits illustrated EC50 values of 15 and 224 nM.
机译：过氧化物酶体增殖物激活受体γ（PPARgamma）激活剂最近在2型糖尿病的临床管理中引起了极大的关注，促使人们进行了许多尝试来发现和优化新的PPARgamma激活剂。考虑到这一点，我们使用七套不同的激活剂探索了PPARgamma的药效空间。随后，采用遗传算法和多元线性回归分析来选择能够访问自洽和预测的定量构效关系（QSAR）的药效学模型和二维物理化学描述子的最佳组合（r2（71）= 0.80，F = 270.3 ，r2LOO = 0.73，针对17种外部测试抑制剂的r2PRESS = 0.67）。 QSAR方程中出现了三个正交药效基团，并通过接收器工作特征（ROC）曲线分析进行了验证。然后将这些模型用于筛选美国国家癌症研究所（NCI）的化合物清单。排名最高的命中是在体外测试的。最有效的结果表明EC50值为15和224 nM。

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